A novel method for automatic strategy acquisition in N-player non-zero-sum games

Phelps, Steve; Marcinkiewicz, Marek; Parsons, Simon

doi:10.1145/1160633.1160760

Cited by 28 publications

(25 citation statements)

References 10 publications

(11 reference statements)

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“…In recent work [75,77] we attack this problem by introducing an algorithm called fish+ for searching for new heuristic strategies within an iterative mechanism-design context. Conventional approaches to strategy optimisation use a strategy's payoff as the basis of an objective function.…”

Section: Iterative Refinement Of Heuristic-strategy Analysismentioning

confidence: 99%

Evolutionary mechanism design: a review

Phelps

McBurney

Parsons

2009

Auton Agent Multi-Agent Syst

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The advent of large-scale distributed systems poses unique engineering challenges. In open systems such as the internet it is not possible to prescribe the behaviour of all of the components of the system in advance. Rather, we attempt to design infrastructure, such as network protocols, in such a way that the overall system is robust despite the fact that numerous arbitrary, non-certified, third-party components can connect to our system. Economists have long understood this issue, since it is analogous to the design of the rules governing auctions and other marketplaces, in which we attempt to achieve sociallydesirable outcomes despite the impossibility of prescribing the exact behaviour of the market participants, who may attempt to subvert the market for their own personal gain. This field is known as "mechanism design": the science of designing rules of a game to achieve a specific outcome, even though each participant may be self-interested. Although it originated in economics, mechanism design has become an important foundation of multi-agent systems (MAS) research. In a traditional mechanism design problem, analytical methods are used to prove that agents' game-theoretically optimal strategies lead to socially desirable outcomes. In many scenarios, traditional mechanism design and auction theory yield clear-cut results; however, there are many situations in which the underlying assumptions of the theory areWe are grateful for financial support received from the UK EPSRC through the Market-Based Control of Complex Computational Systems Project 123 238 Auton Agent Multi-Agent Syst (2010) 21:237-264 violated due to the messiness of the real-world. In this paper we review alternative approaches to mechanism design which treat it as an engineering problem and bring to bear engineering design principles, viz.: iterative step-wise refinement of solutions, and satisficing instead of optimization in the face of intractable complexity. We categorize these approaches under the banner of evolutionary mechanism design.

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Section: Iterative Refinement Of Heuristic-strategy Analysismentioning

confidence: 99%

Evolutionary mechanism design: a review

Phelps

McBurney

Parsons

2009

Auton Agent Multi-Agent Syst

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“…What's more, a technique called perturbation analysis is used to evaluate whether a strategy can be improved further. Phelps et al [33,34] successfully applied this approach in acquiring a better trading strategy for da markets. Jordan et al [17] took a similar approach to the evaluation of entries in the tac Supply Chain Management Tournament (scm) and other games [16].…”

Section: Strategy Evaluation In Competitive Gamesmentioning

confidence: 99%

“…For instance, entrant A beating B in a bilateral game does not necessarily imply that A would still beat B when an additional entrant C joins the game, no matter whether C uses either of the specialists used by A and B, or a third, new specialist. This suggests, for example, that the replicator dynamics fields reported in [34] based on 6-agent auction games or in [17] based on 6-agent tac scm games are likely to change when a different set of game profiles are used.…”

Section: Targeting Chargesmentioning

confidence: 99%

“…Although these evolutionary or adaptive approaches involve automatic processes, they make use of an array of candidate auction rules or parameterizable frameworks that are initially conceived by humans. Moreover, the result of an evolutionary exploration or an adaptive process, may depend on the quality of the candidate solutions which the process starts with-this was certainly the experience we had in [31] and [34].…”

Section: Introductionmentioning

confidence: 97%

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What the 2007 TAC Market Design Game tells us about effective auction mechanisms

Niu

Cai

Parsons

et al. 2009

Auton Agent Multi-Agent Syst

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This paper analyzes the entrants to the 2007 tac Market Design Game. We present a classification of the entries to the competition, and use this classification to compare these entries. The paper also attempts to relate market dynamics to the auction rules adopted by these entries and their adaptive strategies via a set of post-tournament experiments. Based on this analysis, the paper speculates about the design of effective auction mechanisms, both in the setting of this competition and in the more general case.

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“…Non-zero-sum game theory is a typical game theory to solve many problems in biology, economics, computer science, political science, military strategy, and many other disciplines [1]. In non-zero-sum game, the sum of what each player gets or losses is not zero.…”

Section: Introductionmentioning

confidence: 99%